Browse: 🏠 · Solutions · Connectors · Methods · Tables · Content · Parsers · ASIM Parsers · ASIM Products · Logic Apps · 📊
| Attribute | Value |
|:----------|:------|
| Connector ID | VectraXDR |
| Publisher | Vectra |
| Used in Solutions | Vectra XDR |
| Collection Method | Azure Function |
| Connector Definition Files | VectraXDR_API_FunctionApp.json |
| Ingestion API | Log Ingestion API — Sibling ARM template declares DCR / Log Ingestion API resources|Azure Function code contains both Log Ingestion API and HTTP Data Collector API patterns |
| Microsoft Learn | View on Learn |
The Vectra XDR connector gives the capability to ingest Vectra Detections, Audits, Entity Scoring, Lockdown, Health and Entities data into Microsoft Sentinel through the Vectra REST API. Refer to the API documentation: https://support.vectra.ai/s/article/KB-VS-1666 for more information.
This connector ingests data into the following tables:
| Table | Transformations | Ingestion API | Lake-Only |
|---|---|---|---|
Audits_Data_CL |
✓ | ✓ | ✓ |
Detections_Data_CL |
✓ | ✓ | ✓ |
Entities_Data_CL |
✓ | ✓ | ✓ |
Entity_Scoring_Data_CL |
✓ | ✓ | ✓ |
Health_Data_CL |
✓ | ✓ | ✓ |
Lockdown_Data_CL |
✓ | ✓ | ✓ |
💡 Tip: Tables with Ingestion API support allow data ingestion via the Azure Monitor Data Collector API, which also enables custom transformations during ingestion.
Resource Provider Permissions:
Custom Permissions:
https://support.vectra.ai/s/article/KB-VS-1666.⚠️ Note: These instructions were automatically generated from the connector's user interface definition file using AI and may not be fully accurate. Please verify all configuration steps in the Microsoft Sentinel portal.
NOTE: This connector uses Azure Functions to connect to the Vectra API to pull its logs into Microsoft Sentinel. This might result in additional data ingestion costs. Check the Azure Functions pricing page for details.
(Optional Step) Securely store workspace and API authorization key(s) or token(s) in Azure Key Vault. Azure Key Vault provides a secure mechanism to store and retrieve key values. Follow these instructions to use Azure Key Vault with an Azure Function App.
NOTE: This data connector depends on a parser based on a Kusto Function to work as expected. Follow these steps for Detections Parser, Audits Parser, Entity Scoring Parser, Lockdown Parser and Health Parser to create the Kusto functions alias, VectraDetections, VectraAudits, VectraEntityScoring, VectraLockdown and VectraHealth.
STEP 1 - Configuration steps for the Vectra API Credentials
Follow these instructions to create a Vectra Client ID and Client Secret.
STEP 2 - App Registration steps for the Application in Microsoft Entra ID
This integration requires an App registration in the Azure portal. Follow the steps in this section to create a new application in Microsoft Entra ID:
Reference link: https://learn.microsoft.com/azure/active-directory/develop/quickstart-register-app
STEP 3 - Add a client secret for application in Microsoft Entra ID
Sometimes called an application password, a client secret is a string value required for the execution of Vectra Data Connector. Follow the steps in this section to create a new Client Secret:
Reference link: https://learn.microsoft.com/azure/active-directory/develop/quickstart-register-app#add-a-client-secret
STEP 4 - Get Object ID of your application in Microsoft Entra ID
After creating your app registration, follow the steps in this section to get Object ID:
STEP 5 - Assign role of Contributor to application in Microsoft Entra ID
Follow the steps in this section to assign the role:
User, group, or service principal.Reference link: https://learn.microsoft.com/azure/role-based-access-control/role-assignments-portal
STEP 6 - Create a Keyvault
Follow these instructions to create a new Keyvault.
STEP 7 - Create Access Policy in Keyvault
Follow these instructions to create access policy in Keyvault.
Note: **Ensure the Permission model in the Access Configuration of Key Vault is set to **'Vault access policy'
STEP 8 - Choose ONE from the following two deployment options to deploy the connector and the associated Azure Function
IMPORTANT: Before deploying the Vectra data connector, have the Vectra API Authorization Credentials readily available..
9. Option 1 - Azure Resource Manager (ARM) Template
Use this method for automated deployment of the Vectra connector.
Click the Deploy to Azure button below.
Select the preferred Subscription, Resource Group and Location.
Enter the below information :
Function Name
Workspace Name
Vectra Base URL (https://
Mark the checkbox labeled I agree to the terms and conditions stated above.
Click Purchase to deploy.
10. Option 2 - Manual Deployment of Azure Functions
Use the following step-by-step instructions to deploy the Vectra data connector manually with Azure Functions (Deployment via Visual Studio Code).
1. Deploy a Function App
NOTE: You will need to prepare VS code for Azure function development.
Download the Azure Function App file. Extract archive to your local development computer.
Start VS Code. Choose File in the main menu and select Open Folder.
Select the top level folder from extracted files.
Choose the Azure icon in the Activity bar, then in the Azure: Functions area, choose the Deploy to function app button. If you aren't already signed in, choose the Azure icon in the Activity bar, then in the Azure: Functions area, choose Sign in to Azure If you're already signed in, go to the next step.
Provide the following information at the prompts:
a. Select folder: Choose a folder from your workspace or browse to one that contains your function app.
b. Select Subscription: Choose the subscription to use.
c. Select Create new Function App in Azure (Don't choose the Advanced option)
d. Enter a globally unique name for the function app: Type a name that is valid in a URL path. The name you type is validated to make sure that it's unique in Azure Functions. (e.g. VECTRAXXXXX).
e. Select a runtime: Choose Python 3.8 or above.
f. Select a location for new resources. For better performance and lower costs choose the same region where Microsoft Sentinel is located.
Deployment will begin. A notification is displayed after your function app is created and the deployment package is applied.
Go to Azure Portal for the Function App configuration.
2. Configure the Function App
https://<CustomerId>.ods.opinsights.azure.us.📄 Source: [Vectra XDR\Data Connectors\VectraDataConnector\README.md](https://github.com/Azure/Azure-Sentinel/blob/master/Solutions/Vectra XDR\Data Connectors\VectraDataConnector\README.md)
This folder contains the Azure function time trigger code for Vectra XDR Data Connector. The connector will run periodically and ingest the Vectra XDR data into the Microsoft Sentinel logs custom tables.
VectraDataConnector/ - This contains the package, requirements, ARM JSON file, connector page template JSON, and other dependencies.
Detections/ - This contains the Azure function source code to ingest the data of the below mentioned endpoint.
Audits/ - This contains the Azure function source code to ingest the data of the below mentioned endpoint.
EntityScoring/ - This contains the Azure function source code to ingest the data of the below mentioned endpoint.
Health/ - This contains the Azure function source code to ingest the data of the below mentioned endpoint.
Lockdown/ - This contains the Azure function source code to ingest the data of the below mentioned endpoint.
After the solution is published, we can find the connector in the connector gallery of Microsoft Sentinel among other connectors in the Data connectors section of Sentinel.
i. Go to Microsoft Sentinel -> Data Connectors
ii. Click on the Vectra XDR Data Connector, and the connector page will open.
iii. Click on the blue Deploy to Azure button.
It will lead to a custom deployment page where the user needs to select Subscription, Resource Group, and Location. Then the following information is required to configure the Vectra Data Connector.
| User Inputs | Default Value |
|---|---|
| Function Name | Vectra |
| Workspace ID | None |
| Workspace Key | None |
| Vectra Base URL | None |
| Vectra Client Id - Health | None |
| Vectra Client Secret Key - Health | None |
| Vectra Client Id - Entity Scoring | None |
| Vectra Client Secret Key - Entity Scoring | None |
| Vectra Client Id - Detections | None |
| Vectra Client Secret Key - Detections | None |
| Vectra Client Id - Audits | None |
| Vectra Client Secret Key - Audits | None |
| Vectra Client Id - Lockdown | None |
| Vectra Client Secret Key - Lockdown | None |
| Start Time | None(Last 24 Hour) |
| Audits Table Name | Audits_Data |
| Detections Table Name | Detections_Data |
| Entity Scoring Table Name | Entity_Scoring_Data |
| Lockdown Table Name | Lockdown_Data |
| Health Table Name | Health_Data |
| Log Level | INFO |
| Lockdown Schedule | 0 0/10 * * * * |
| Health Schedule | 0 1/10 * * * * |
| Detections Schedule | 0 2/10 * * * * |
| Audits Schedule | 0 5/10 * * * * |
| Entity Scoring Schedule | 0 8/10 * * * * |
The connector should start ingesting the Vectra XDR data into the tables at every time interval specified in the Schedules during configuration.
i. Log in to the Azure portal using the URL - Azure Portal-Home.
ii. Go to Microsoft Sentinel -> Data Connectors
iii. Click the “import” button at the top and select the JSON file VectraXDR_API_FunctionApp.json` downloaded on your local machine from Github.
iv. This will load the connector page, and the rest of the process will be the same as the Installing for users guideline above.
Each invocation and its logs of the function can be seen in the Function App service of Azure, available in the Azure Portal outside the Microsoft Sentinel.
i. Go to Function App and click on the function which you have deployed, identified with the given name at the deployment stage.
ii. Go to Functions -> Any of our function -> Monitor
iii. By clicking on the invocation time, you can see all the logs for that run.
Note: Furthermore, we can check logs in Application Insights of the given function in detail if needed. We can search the logs by operation ID in the Transaction search section.
Browse: 🏠 · Solutions · Connectors · Methods · Tables · Content · Parsers · ASIM Parsers · ASIM Products · Logic Apps · 📊